Finance and Economics Discussion Series: Accessible versions of figures for 2020-033

Health Insurance and Hospital Supply: Evidence from 1950s Coal Country

Accessible version of figures


Figure 1: County Mining Employment in 1950 as a Share of Population Age 14 and Older in the Appalachian Region
Notes: The counties within the blue bolded line are considered Appalachia. Counties are defined as part of Appalachia using the Appalachian Regional Commission's (ARC) 1967 definition of Appalachian counties. Only states with at least one county in Appalachia are included in the figure. The fraction of mining employment in each county is calculated as the fraction of individuals employed in mining divided by total county population age 14 and older.
Source: Authors' calculations using data from the United States County and City Data Book Consolidated File and data from the ARC 1967 provided by James Ziliak.

County map of all states with at least one county in the federally designated geographic region of Appalachia, which is county-by-county. States include Alabama, Georgia, Kentucky, Maryland, Mississippi, New York, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia, West Virginia. Counties are defined as part of Appalachia using the Appalachian Regional Commission’s (ARC) 1967 definition of Appalachian counties. Thick blue line shows border of Appalachian region in these states. The counties within the blue bolded line are considered Appalachia. Counties are shaded to represent the share of population 14 and older employed in mining. Darker shades represent higher mining employment. The fraction of mining employment in each county is calculated as the fraction of individuals employed in mining divided by total county population age 14 and older in 1950. Every state in Appalachia has at least one county with mining employment. The biggest concentrations of mining employment are in the eastern part of Kentucky and southwest part of West Virginia.

Return to text.


Figure 2: Locations of the United Mine Workers Hospitals and the County Mining Employment as a Share of Population Age 14 and Older in Central Appalachia
Notes: Only Appalachia counties in states in Central Appalachia are included. The United Mine Workers of America (UMWA) opened ten state-of-the-art hospitals in central Appalachia in 1956, known as the Miners' Memorial Hospitals, indicated by the green triangles in the map. The UMWA hospitals were opened in ten counties with a high concentration of health insurance coverage. While these hospitals were run by the UMWA, the hospitals served both miners and non-miners.
Source: Authors' calculations using data from the United States County and City Data Book Consolidated File and hospital location based on Ford et al. (1962).

County-level map of Appalachian counties in states in Central Appalachia are included (West Virginia, Kentucky, Virginia, and Tennessee). Counties are shaded to represent the share of population 14 and older employed in mining. Darker shades represent higher mining employment. Green triangles represent the locations of the ten state-of-the-art United Mine Workers of America hospitals in Central Appalachia in 1956, known as the Miners’ Memorial Hospitals. Hospitals are in counties in Eastern Kentucky, southern West Virginia, and Western Virginia. These counties have high shares of mining employment in the population 14 years and older, meaning the hospitals opened in counties with a high concentration of the union health insurance coverage. The green triangles are in counties that are also shaded darker to represent the high concentration of mining employment. While these hospitals were run by the UMWA, the hospitals served both miners and non-miners.

Return to text.


Figure 3: Timeline of Interventions
Notes: The United Mine Workers of America (UMWA) began providing free hospital care insurance in June 1950 and opened ten state-of-the-art hospitals in central Appalachia in late 1955 and 1956. We chose 1946 as the starting year of our analysis period because 1946 marks the beginning of the post-World War II period. We chose 1965 as the last year in our analysis period to avoid confounding effects from the introduction of Medicare and Medicaid in 1966.
Source: Authors' illustration.

Timeline to depict the rollout of the two union health care interventions. A horizontal line shows years starting in 1946 and ending in 1965, the years in the data analysis sample. Two vertical dashed lines represent the years that each intervention began: 1950 for the insurance and 1956 for the hospitals. Under the horizontal line with the years 1946-1965 are two rows, one for the insurance intervention and one for the hospitals intervention. Each row depicts the pre- and post- periods for the corresponding intervention. For the insurance (top row), the pre-period is indicated by a bracket running from 1946-1949. The post period is indicated by a bracket running from 1950-1956. Below the insurance row is the hospital row. The pre-period for the hospital intervention is 1951-1955. The post period is 1956-1965. There is an overlap between the post-period for the insurance and part of the pre-period for the hospitals between 1951 and 1955. The United Mine Workers of America (UMWA) began providing free hospital care insurance in June 1950 and opened ten state-of-the-art hospitals in central Appalachia in late 1955 and 1956. We chose 1946 as the starting year of our analysis period because 1946 marks the beginning of the post-World War II period. We chose 1965 as the last year in our analysis period to avoid confounding effects from the introduction of Medicare and Medicaid in 1966.

Return to text.


Figure 4: Effects of UMWA Programs on Health Care Utilization
Notes: Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with treatment variable. The bars show the 95 percent confidence interval of the coefficient estimates. In the left figures, the sample includes years from 1946 to 1956 and the treatment variable is the fraction of mining employment of each county in 1950. In the right figures, the sample includes years from 1951 to 1965 and the treatment variable is a dummy variable for a UMWA hospital. The dashed lines indicate the year of the interventions - 1950 for the insurance intervention and 1956 for the completion of the hospitals. Standard errors are clustered at the county level. Control variables included in the regression are the number of births of residence in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1948 in the right graph and 1955 in the left graph), and county fixed effects. In addition, the figures on the left include an interaction between the post indicator (equal to one for years 1950 and later) and the total number of births. To correct for differences in the county-year error term and improve precision, we estimate the regressions using Weighted Least Squares. The analysis in (a) is weighted by county-level births and the analysis in (b) is weighted by county-level population.
Source: Authors' calculation using data from the U.S. Vital Statistics, Hill-Burton Project Register, the American Hospital Association's annual survey, and the United States County and City Data Book Consolidated File.

Four graphs of event-study regression coefficients over time for hospital birth rates (panel a) and hospital admissions/1,000 (panel b). Each panel has two graphs, left and right. The left graphs in both panels show regression results for the insurance intervention. The sample includes years from 1946 to 1955 and the treatment variable is the share of mining employment in population 14 years and older in each county in 1950. Coefficients must be scaled by 0.03, the average Appalachian county-level share of mining employment in population 14 years and older in 1950. The right graphs in both panels show regression results for the effects of the union hospital intervention in high insurance areas. The sample includes years from 1951 to 1965 and the treatment variable is a dummy variable for a UMWA hospital. The dashed lines indicate the year of the interventions – 1950 for the insurance intervention and 1956 for the completion of the union hospitals. Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with treatment variable (an event study specification). The bars show the 95 percent confidence interval of the coefficient estimates. Panel (a) shows results for the effects of the insurance (left graph) and the hospitals (right graph) on hospital birth rates. The left graph shows that hospital birth rates have no consistent pre-trends before the insurance began in 1950. The event-study coefficients then jump up to around 0.50 in 1951 then to nearly 1 by 1952, both statistically different from zero. The right graph shows no significant additional effect of the union hospitals on hospital birth rates. Panel (b) shows results for the effects of the insurance (left graph) and the hospitals (right graph) on hospital admissions per 1,000. The left graph shows that hospital admissions increase by around 80 per 1,000 in 1951, but the effects taper off over time to around 13 per 1,000 by 1955. Individual coefficients are not statistically different from zero. The right graph shows no clear impact of the hospitals on additional hospital admissions.
Standard errors are clustered at the county level. Control variables included in the regression are the number of births of residence in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1948 in the right graph and 1955 in the left graph), and county fixed effects. In addition, the figures on the left include an interaction between the post indicator (equal to one for years 1950 and later) and the total number of births. To correct for differences in the county-year error term and improve precision, we estimate the regressions using Weighted Least Squares. The analysis in (a) is weighted by county-level births and the analysis in (b) is weighted by county-level population.

Return to text.


Figure 5: Effects of UMWA Programs on Mortality
Notes: Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with each treatment variable. The bars show the 95 percent confidence interval of the coefficient estimates. In the left figures, the sample includes years 1946- 1956 and the treatment variable is the fraction of mining employment of each county in 1950. In the right figures, the sample includes years from 1951 to 1965 and the treatment variable is a dummy variable for a UMWA hospital. The dashed lines indicate the year of the interventions - 1950 for the insurance intervention and 1956 for the completion of the hospitals. Standard errors are clustered at the county level. Control variables included in the regression are the number of births of residents in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1948 in the right graph and 1955 in the left graph), and county fixed effects. In addition, the figures on the left include an interaction between the post indicator (equal to one for years 1950 and later) and the total number of births. To correct for differences in the county-year error term and improve precision, we estimate the regressions using Weighted Least Squares. The analysis in (a) is weighted by county-level births and the analysis in (b) is weighted by county-level population.
Source: Authors' calculation using data from the U.S. Vital Statistics, Hill-Burton Project Register, the American Hospital Association's annual survey, and the United States County and City Data Book Consolidated File.

Four graphs of event-study regression coefficients over time for infant mortality per 1,000 births (Panel a) and overall mortality per 1,000 population Panel b). Each panel has two graphs, left and right. The left graphs in both panels show regression results for the insurance intervention. The sample includes years from 1946 to 1955 and the treatment variable is the share of mining employment in population 14 years and older in each county in 1950. Coefficients must be scaled by 0.03, the average Appalachian county-level share of mining employment in population 14 years and older in 1950. The right graphs in both panels show regression results for the additional effects of hospital intervention in high insurance areas. The sample includes years from 1951 to 1965 and the treatment variable is a dummy variable for a UMWA hospital. The dashed lines indicate the year of the interventions – 1950 for the insurance intervention and 1956 for the completion of the hospitals. Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with treatment variable (an event study specification). The bars show the 95 percent confidence interval of the coefficient estimates. Panel (a) shows results for the effects of the insurance (left graph) and the hospitals (right graph) on infant mortality rates. The left graph shows some evidence of pre-trends, as one out of the four event study coefficients in the pre-period is statistically different from zero. The coefficients in the post-period after 1950 show a clear downward trend, starting with 22 fewer infant deaths per 1,000 in 1950 and ending with 50 fewer by 1955 for counties with 100 percent mining employment compared to those with zero mining employment. The right graph shows no significant additional effect of the hospitals on infant mortality rates, and clear evidence of pre-trends. Panel (b) shows results for the effects of the insurance (left graph) and the hospitals (right graph) on overall mortality per 1,000 population. The left graph clear evidence of pre-trends and large standard errors. The right graph shows no clear impact of the hospitals on overall mortality.
Standard errors are clustered at the county level. Control variables included in the regressions are the number of births of residence in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1948 in the right graph and 1955 in the left graph), and county fixed effects. In addition, the figures on the left include an interaction between the post indicator (equal to one for years 1950 and later) and the total number of births. To correct for differences in the county-year error term and improve precision, we estimate the regressions using Weighted Least Squares. The analysis in (a) is weighted by county-level births and the analysis in (b) is weighted by county-level population.

Return to text.


Figure 6: Effects of UMWA Programs on Inputs to Hospital Supply
Notes: Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with each treatment variable. The bars show the 95 percent confidence interval of the coefficient estimates. For the estimates of the effect of hospital beds per 1,000, the sample in the left figure of panel (a) includes all years prior to 1956 and the treatment variable is the fraction of mining employment of each county in 1950. In the right figure of panel (a), the sample includes years from 1951 to 1965 and the treatment variable is a dummy variable for a UMWA hospital. For the estimates of the effect on full-time equivalent employees (FTEs) in panel (b), the American Hospitals Association (AHA) hospital survey does not include data on FTEs until 1951. As a result, we cannot perform estimates for the effects of the insurance on FTEs. The dashed lines indicate the year of the interventions - 1950 for the insurance intervention and 1956 for the completion of the hospitals. Standard errors are clustered at the county level. Control variables included in the regression are the number of births of residence in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1948 in the right graph and 1955 in the left graph for the hospital beds per 1,000, and omitting 1955), and county fixed effects. In addition, the left figure of panel (a) includes an interaction between the post indicator (equal to one for years 1950 and later) and the total number of births. To correct for differences in the county-year error term and improve precision, we estimate the regressions using Weighted Least Squares. The analysis in (a) is weighted by county-level births and the analysis in (b) is weighted by county-level population. Source: Authors' calculation using data from the U.S. Vital Statistics, Hill-Burton Project Register, the American Hospital Association's annual survey, and the United States County and City Data Book Consolidated File.

Three graphs of event-study regression coefficients over time for hospital beds per 1,000 (panel a) and full time equivalent employees (FTEs) per 1,000 (panel b). The top panel, panel (a), has two graphs, left and right. The bottom panel, panel (b), has one graph. Panel (a), left graph, shows regression results for the insurance intervention. The sample includes years from 1946 to 1955 and the treatment variable is the share of mining employment in population 14 years and older of each county in 1950. Coefficients must be scaled by 0.03, the average Appalachian county-level share of mining employment in population 14 years and older in 1950. The right graph in panel (a) and the only graph in panel (b) show regression results for the additional effects of hospital intervention in high insurance areas. The sample includes years from 1951 to 1965 and the treatment variable is a dummy variable for a UMWA hospital. The dashed lines indicate the year of the interventions – 1950 for the insurance intervention and 1956 for the completion of the hospitals. Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with treatment variable (an event study specification). The bars show the 95 percent confidence interval of the coefficient estimates. Panel (a) shows results for the effects of the insurance (left graph) and the hospitals (right graph) on hospital beds per 1,000. The left graph, the regression results of the insurance, shows large standard errors and no clear evidence one way or the other that hospital beds increased as a result of the insurance. By contrast, the right graph, the regression results of the union hospitals in high insurance areas, shows clear evidence of a large increase in the total amount of hospital beds that persists over time. There is no evidence of pre-trends before 1956, the year the hospitals opened. Starting in 1956, there is a large, clear increase in the number of beds per 1,000 in UMWA hospital counties of 1.92 per 1,000. The point estimates taper off slightly over time, but remain statistically higher than before the hospital intervention, ending with a point estimate of 1.33 in 1965, not statistically different from the point estimate in 1956. Panel (b) shows results for FTEs. Because the American Hospitals Association (AHA) hospital survey does not include data on FTEs until 1951, we cannot estimate the effect of the insurance on FTEs. Instead, we estimate the effects of the hospitals only on FTEs. The graph shows no evidence of pre-trends before the intervention in 1956. After 1956, the number of FTEs jumps to 3.8 additional FTEs in union hospital counties. The effects begin to taper off starting in 1962, as the union began to make cuts to the insurance program.
Control variables included in the regressions are the number of births of residence in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1948 in the right graph and 1955 in the left graph for the hospital beds per 1,000, and omitting 1955), and county fixed effects. In addition, the left figure of panel (a) includes an interaction between the post indicator (equal to one for years 1950 and later) and the total number of births. To correct for differences in the county-year error term and improve precision, we estimate the regressions using Weighted Least Squares. All three analyses are weighted by county-level population.

Return to text.


Figure 7: Crowd-out Effects of UMWA Hospitals
Notes: Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with each treatment variable. The bars show the 95 percent confidence interval of the coefficient estimates. The sample includes years from 1951 to 1965. Instead of using an indicator for whether a county got a hospital, we instead use the number of additional hospital beds in the new UMWA hospitals in a given county (not the total number of hospital beds, only the new beds in the new UMWA hospitals). The right-hand side is the total beds in a given county (UMWA beds plus other existing hospital beds in each county). The dashed line indicates the year of the intervention -1956 for the completion of the hospitals. Standard errors are clustered at the county level. Control variables included in the regression are the number of births of residence in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1955), and county fixed effects.
Source: Authors' calculation using data from the Hill-Burton Project Register, the American Hospital Association's annual survey, and the United States County and City Data Book Consolidated File.

Each dot represents the coefficient from a county-year regression interacting a set of year fixed effects with each treatment variable. The bars show the 95 percent confidence interval of the coefficient estimates. The sample includes years from 1951 to 1965. Instead of using an indicator for whether a county got a hospital, we instead use the number of additional hospital beds in the new UMWA hospitals in a given county in 1956 (not the total number of hospital beds, only the new beds in the new UMWA hospitals). The right-hand side is the total beds in a given county (UMWA beds plus other existing hospital beds in each county). The dashed line indicates the year of the intervention –1956 for the completion of the hospitals. The coefficients can be interpreted as, for every new UMWA hospital bed, how many total beds in the county were added. This accounts for any crowd out effects of private hospitals reducing their bed capacity in response to the added UMWA beds. There is no clear evidence of pre-trends before 1956. In 1956, for every one new UMWA bed, there were 0.76 total beds, suggesting a crowd-out rate of 0.24. The point estimates grow slightly over time to reach 0.84 by 1965, the end of the sample period. Standard errors are clustered at the county level. Control variables included in the regression are the number of births of residence in the county, the population of the county, and the fraction of mining employment in the county, year fixed effects (omitting 1955), and county fixed effects.

Return to text.


Figure 8: Real Hourly Wages 1947-1965.
Source: Authors' calculation using data from U.S. Department of Labor, Bureau of Labor Statistics. 1991. "Employment, Hours, and Earnings, United States, 1909-1990 Volume 1."

Average real hourly wage in 1982 dollars for coal workers and all non-farm workers for 1947-1965, all of our sample period years except 1946. Top line is coal workers, bottom line is all non-farm workers. Coal workers earn around 30 percent more on average than the average non-farm worker during this period. The gap between the two is relatively stable over time, suggesting no differential increases in wages in high coal employment areas around 1950.

Return to text.


Figure A.1: County Mining Employment as a Share of Total Population Age 14 and Older by County, 1950
Notes: The counties within the blue bolded line are considered Appalachia. The fraction of mining employment in each county is calculated as the fraction of individuals employed in mining divided by total population age 14 and older.
Source: Authors' calculations using data from the United States County and City Data Book Consolidated File.

County level map of entire United States, excluding Alaska and Hawaii. Counties are shaded according to their county-level share of mining employment to population 14 years and older in 1950. Darker shades represent counties with higher mining employment. Counties in Appalachia are outlined in blue, running from mid-Alabama to southern New York. This map is the same as the map in Figure 1, except for the entire US and not just only the states with counties in Appalachia. In the eastern United States, mining is concentrated in the middle portion of Appalachia: in Kentucky, West Virginia, Virginia, and Tennessee, where some counties have up to 95 percent of the population 14 and older employed in mining. The map also shows some mining employment out in the Western states of Nevada, Colorado, Wyoming, Arizona, New Mexico, and Texas.

Return to text.


Figure A.2: Cumulative Hill-Burton Beds Provided per 1,000, 1950 and 1960
Notes: Maps include all states that contain at least one county in the Appalachian Regional Commission's list of counties in Appalachia. Hill-Burton provided beds are defined as the number of cumulative beds each project that received Hill-Burton funding provided. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton beds were provided as the year the project was approved. The number of cumulative Hill-Burton beds is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year.
Source: Authors' calculations using data from the Hill-Burton Project Register and the United States County and City Data Book Consolidated File.

County-level map of all states that contain at least one county in the Appalachian Regional Commission’s list of counties in Appalachia (Appalachian states). Counties are shaded according to the number of Hill-Burton beds provided per 1,000 as of a given year. Counties shaded in white received no Hill-Burton beds. Panel (a) shows 1950 and Panel (b) shows 1960. Hill-Burton provided beds are defined as the number of additional beds each project that received Hill-Burton funding. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton beds were provided as the year the project was approved. The number of Hill-Burton beds is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year. The key takeaway is that the areas where the UMWA built its hospitals in Central Appalachia (Eastern Kentucky, West Virginia, and Eastern Virginia) received little to no Hill-Burton beds both before the UMWA hospitals in 1950 and after the UMWA hospitals were already opened, in 1960. Many of these counties are shaded white in 1950 and are still shaded white in 1960, meaning no Hill-Burton beds in these counties after the program began more than a decade prior.

Return to text.


Figure A.3: Cumulative Hill-Burton Funding per 1,000, 1950 and 1960
Notes: Hill-Burton provided funds are defined as total cumulative Hill-Burton funding each project received through the Hill-Burton program. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton funds were provided as the year the project was approved. The cumulative amount of Hill-Burton funding received is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year.
Source: Authors' calculations using data from the Hill-Burton Project Register and the United States County and City Data Book Consolidated File.

County-level map of all states that contain at least one county in the Appalachian Regional Commission’s list of counties in Appalachia (Appalachian states). Counties are shaded according to the amount of Hill-Burton funding provided per 1,000 people as of a given year. Counties shaded in white received no Hill-Burton funding. Panel (a) shows 1950 and Panel (b) shows 1960. Hill-Burton provided funds are defined as total Hill-Burton funding each project received through the Hill-Burton program. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton funds were provided as the year the project was approved. The amount of Hill-Burton funding received is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year. The key takeaway is that the areas where the UMWA built its hospitals in Central Appalachia (Eastern Kentucky, West Virginia, and Eastern Virginia) received little to no Hill-Burton funding before the UMWA hospitals in 1950. However, some counties in Central Appalachia did receive small amounts of funding by 1960, though the funding was not used on beds, which is evident comparing panel (b) in this figure with panel (b) in the previous Figure A.2. Some counties in Central Appalachia that are shaded white in panel (b) in Figure A.2 are shaded light yellow in panel (b) in this figure, meaning that by 1960, they had received no beds but some funding.

Return to text.


Figure A.4: Cumulative Hill-Burton Beds Provided per 1,000, 1950 and 1960
Notes: Hill-Burton provided beds are defined as the cumulative number of additional beds each project that received Hill-Burton funding provided. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton beds were provided as the year the project was approved. The number of Hill-Burton beds is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year.
Source: Authors' calculations using data from the Hill-Burton Project Register and the United States County and City Data Book Consolidated File.

County-level map of all states in the United States, minus Alaska and Hawaii. Counties are shaded according to the number of Hill-Burton beds provided per 1,000 as of a given year. Panel (a) shows a map for 1960 and panel (b) shows a map for 1950. Counties in white received no Hill-Burton beds. Hill-Burton provided beds are defined as the number of additional beds each project that received Hill-Burton funding provided. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton beds were provided as the year the project was approved. The number of Hill-Burton beds is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year. By 1950, concentrations of Hill Burton beds were scattered in counties throughout the United States, in the Northeast, Southeast, Midwest, and West. By 1960, more counties had received Hill-Burton beds, as the entire map appears darker than in 1950. Again, beds were not concentrated in any particular region, with counties throughout the country receiving funds. One exception is Central Appalachia, as shown in Figure A.2. By 1960, there is a noticeable “hole” in the map, i.e. a concentration of counties shaded in white meaning they received no Hill-Burton beds, in Central Appalachia (Eastern Kentucky, West Virginia, and Virginia). There are few other such “holes” without any beds in the rest of the United States, except some areas in the Western States.

Return to text.


Figure A.5: Cumulative Hill-Burton Funding Provided per 1,000, 1950 and 1960
Notes: Hill-Burton provided funds are defined as total cumulative Hill-Burton funding each project received through the Hill-Burton program. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton funds were provided as the year the project was approved. The amount of Hill-Burton funding received is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year.
Source: Authors' calculations using data from the Hill-Burton Project Register and City Data Book Consolidated File.

County-level map of all states in the United States, minus Alaska and Hawaii. Counties are shaded according to the amount of Hill-Burton funds provided per 1,000 as of a given year. Counties in white received no Hill-Burton funds. Panel (a) shows a map for 1960 and panel (b) shows a map for 1950. Hill-Burton provided funds are defined as the number of funds for each project that received Hill-Burton funding. Because the Hill-Burton Project Register only provides data on when the project received initial approval from the Public Health Service Regional Offices, we define the year in which the Hill-Burton funds were provided as the year the project was approved. The amount of Hill-Burton funding received is divided by the population in county in the relevant year. The cutoffs are defined as the quintiles of those counties that received at least some Hill-Burton funding as of the relevant year. By 1950, concentrations of Hill Burton funds were scattered in counties throughout the United States, in the Northeast, Southeast, Midwest, and West. By 1960, more counties had received Hill-Burton beds, as the entire map appears darker than in 1950. There is some concentration of funds in the Deep South compared to the rest of the country. However, some counties in Central Appalachia did receive small amounts of funding by 1960, though the funding was not used on beds, which is evident comparing panel (b) in this figure with panel (b) in the previous Figure A.4. Some counties in Central Appalachia that are shaded white in panel (b) in Figure A.4 are shaded light yellow in panel (b) in this figure, meaning that by 1960, they had received no beds but some funding.

Return to text.